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Advances in legume systematics 14. Classification of Caesalpinioideae. Part 2: Higher-level classification. Author(s): BRUNEAU, A.; QUEIROZ, L. P. de; RINGELBERG, J. J.; BORGES, L. M.; BORTOLUZZI, R. L. da C.; BROWN, G. K.; CARDOSO, D. B. O. S.; CLARK, R. P.; CONCEIÇÃO, A. de S.; COTA, M. M. T.; DEMEULENAERE, E.; STEFANO, R. D. de; EBINGER, J. E.; FERM, J.; FONSECA-CORTÉS, A.; GAGNON, E.; GRETHER, R.; GUERRA, E.; HASTON, E.; HERENDEEN, P. S.; HERNÁNDEZ, H. M.; HOPKINS, H. C. F.; HUAMANTUPA-CHUQUIMACO, I.; HUGHES, C. E.; ICKERT-BOND, S. M.; IGANCI, J.; KOENEN, E. J. M.; LEWIS, G. P.; LIMA, H. C. de; LIMA, A. G. de; LUCKOW, M.; MARAZZI, B.; MASLIN, B. R.; MORALES, M.; MORIM, M. P.; MURPHY, D. J.; O’DONNELL, S. A.; OLIVEIRA, F. G.; OLIVEIRA, A. C. da S.; RANDO, J. G.; RIBEIRO, P. G.; RIBEIRO, C. L.; SANTOS, F. da S.; SEIGLER, D. S.; SILVA, G. S. da; SIMON, M. F.; SOARES, M. V. B.; TERRA, V. Caesalpinioideae is the second largest subfamily of legumes (Leguminosae) with ca. 4680 species and 163 genera. It is an ecologically and economically important group formed of mostly woody perennials... ... Repository: BDPA Publication year: 2024
Soil classification from visible/near-infrared diffuse reflectance spectra at multiple depths. Author(s): VASQUES, G. de M.; DEMATTE, J. A. M.; LOPEZ, L. R.; TERRA, F. da S. Abstract : Visible/near-infrared diffuse reflectance spectroscopy (VNIRS) offers an alternative to conventional analytical methods to estimate various soil attributes. However, the use of VNIRS in soi... ... Repository: BDPA Publication year: 2011
Automatic classification of soybean diseases based on digital images of leaf symptoms. Author(s): BARBEDO, J. G. A.; GODOY, C. V. This paper presents an algorithm for automatic classification of diseases that produce symptons in soybean leaves. Repository: BDPA Publication year: 2015
The roles of textural images in improving land-cover classification in the Brazilian Amazon. Author(s): LU, D.; LI, G.; MORAN, E.; DUTRA, L.; BATISTELLA, M. Texture has long been recognized as valuable in improving land-cover classification, but how data from different sensors with varying spatial resolutions affect the selection of textural images is poo... ... Repository: BDPA Publication year: 2014
Brazilian Soil Classification System. Author(s): SANTOS, H. G. dos; JACOMINE, P. K. T; ANJOS, L. H. C. dos; OLIVEIRA, V. A. de; LUMBRERAS, J. F.; COELHO, M. R.; ALMEIDA, J. A. de; ARAUJO FILHO, J. C. de; OLIVEIRA, J. B. de; CUNHA, T. J. F. Diagnostic attributes and other attributes; Diagnostic surface horizons and diagnostic subsurface horizons; Categorical levels of the system, nomenclature of classes, bases and criteria, concept and d... ... Repository: BDPA Publication year: 2018
Streamlined approaches for image classification using principal component analysis and hierarchical clustering of extrudates from coffee and sorghum blends. Author(s): HIDALGO CHÁVEZ, D. W.; SILVA, F. L. C. DA; PINTO, R. V.; CARVALHO, C. W. P. de; FREITAS-SILVA, O. This article describes simple methods to group images including principal component analysis (PCA) and hierarchical clustering of principal components (HCPC). Images of expanded and low expanded extru... ... Repository: BDPA Publication year: 2023
A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Author(s): LI, G.; LU, D.; DUTRA, L.; BATISTELLA, M. This paper explores the use of ALOS (Advanced Land Observing Satellite) PALSARL-band (Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 C-band data for land-cover classification in a t... ... Repository: BDPA Publication year: 2012
Ecological classification of Brazilian earthworms: a first attempt using morphological data. Author(s): ANDRADE, D. P. de; BROWN, G. G.; CALLAHAM JÚNIOR, M. A. Repository: BDPA Publication year: 2010
Comparison of classification algorithms of images for the mapping of the land covering in Tasso Fragoso municipality, Brazil. Author(s): PEREIRA, P. R. M.; COSTA, F. W. D.; BOLFE, E. L.; MACARRINGE, L.; BOTELHO, A. C. Abstract. One of the main applications of satellite images is the characterization of terrestrial coverage, that from the use of classification techniques, allows the monitoring of spatial transformat... ... Repository: BDPA Publication year: 2021
Andrological classification of bulls evaluated by machine learning. Author(s): ISLER, S. A.; ABREU, U. G. P. de; NOGUEIRA, E.; WEBER, V. A. de M.; PEDRO, F. de O.; ROSCHEL, M. S.; STERZA, F. de A. M; CORDEIRO, D. A. G.; WEBER, F. de L. Repository: BDPA Publication year: 2024

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